Open Source Python Earth Sciences Software
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Python Earth Sciences Software
View 164 business solutionsBrowse free open source Python Earth Sciences Software and projects below. Use the toggles on the left to filter open source Python Earth Sciences Software by OS, license, language, programming language, and project status.
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Madagascar is a software package for geophysical data processing and reproducible numerical experiments. The package mission is to provide a convenient environment for researchers working with digital image and data processing in geophysics and related fields.
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Astropy
Repository for the Astropy core package
The Astropy Project is a community effort to develop a common core package for Astronomy in Python and foster an ecosystem of interoperable astronomy packages. Astropy is a Python library for use in astronomy. Learn Astropy provides a portal to all of the Astropy educational material through a single dynamically searchable web page. It allows you to filter tutorials by keywords, search for filters, and make search queries in tutorials and documentation simultaneously. The Anaconda Python Distribution includes Astropy and is the recommended way to install both Python and the Astropy package. The astropy package contains key functionality and common tools needed for performing astronomy and astrophysics with Python. It is at the core of the Astropy Project, which aims to enable the community to develop a robust ecosystem of affiliated packages covering a broad range of needs for astronomical research, data processing, and data analysis. -
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GPlates
Interactive visualization of plate tectonics.
GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts. -
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eemod_dnsmod
A detailed nitrogen model inside of a simple ecological model
This is an simple ecological model for lakes and reservoirs that contains a very detailed description of the most relevant nitrogen processes. The model is not very complete, but the main intention is to develop a library to be coupled with other models and use the full-mixed model as a testing version. A lot of things can be improved. I will read all the suggestions but I cannot promise that I will include all of them. Every new part of the code will contain the name of the author. If someone contributes improving the capabilities of this model in a substantial way, I will include that person as co-author of the model in the next version release. I hope this will promote people to contribute. Of course, fixing bugs or minor changes will also be mentioned with the corresponding author. Thanks a lot. I hope this can be the seed of a Open Source Community of Ecological Modellers. -
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Platform providing the support for Wireless Sensor Networks in the domain of Natural Hazards as a Service. The objective of the WSN platform is monitoring the behaviour of rockfall barriers, rockfall netting, rock sheds and other protection systems
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Autoplot
Autoplot is an interactive browser for data on the web
Autoplot is an interactive browser for data on the web. Give Autoplot a URL or local file name and it creates a sensible plot of the data. Autoplot allows you to interactively browse data stored in ascii, .cdf, netcdf, and many other formats. Autoplot's source has been moved to GitHub. Thanks to SourceForge for many years of hosting! -
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CAIRO for AERMOD
AERMOD, visualisation, input, modelling and compiling tool
CAIRO for AERMOD v1.1 by MSc Dominik Subotić Simplified training software Avaliable: www.sourceforge.net/projects/cairo-for-aermod/ QGIS plugin: CAIROforAERMOD (Coming 2025.) Tutorial: https://www.youtube.com/watch?v=DZnsJuu1zLc AERMAP, AERMOD and AERPLOT analysis tool and input file compiler. Features: Automatic input by copying coordinates (Google Maps or text) and automatic conversion to UTM. Sources are automatically visualised in Google Earth. Input is done through user interface and automatically compiled into correct syntax and project/file structure. Windows application, supports up to 3 averaging periods, maxtable, maxifile, rankfile and plotfile. Elevation and meteorological data is third party. CAIRO for AERMOD (Compile AERMAP, AERMOD and AERPLOT Input and Run Output) aimed at streamlining the process of making complex input file, with unique syntax and running them. While obviating the need to manually write inputs and running the program through Shell -
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openGPR is a framework for the management, processing and 2D/3D-visualization of ground penetrating radar (GPR, georadar) data. It interoperates with existing tools like Seismic Unix, with a special focus on georadar applications.
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ALAMODE
Ab initio simulator for thermal transport and lattice anharmonicity
ALAMODE is designed for analyzing lattice anharmonicity and lattice thermal conductivity of solids. By using an external DFT package such as VASP and Quantum ESPRESSO, you can extract harmonic and anharmonic force constants straightforwardly with ALAMODE. Using the anharmonic force constants, you can also calculate lattice thermal conductivity from first principles. For more information about ALAMODE, please visit the following webpages: Documentation : http://alamode.readthedocs.io/en/latest/ git repository : https://github.com/ttadano/alamode -
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GDAL wheels for linux
GDAL wheels for python and C/C++ projects (Linux only)
To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs (usually this folder resides inside python site-packages) To compile your own wheels see information given at forefather project: https://github.com/youngpm/gdalmanylinux Usually this is done via command `make wheels` GDAL wheels for Windows are provided by Christoph Gohlke at https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal Built with PROJ (proj.db is included), GEOS, EXPAT. See Dockerfile.wheels for additional components. -
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WARNING! HPGL source code (NOT the releases, they are still here) now moved to the GitHub at https://github.com/hpgl/hpgl. Please, update your bookmarks!
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GEOMS2
Geostatistics and geosciences modeling software
GEOMS2 is a geostatistics and geosciences modeling software. Provides interface for grid (mesh), point, surface and data (non-spatial) objects. It has a 3D viewer and 2D plots using the well known Python engines Mayavi and Matplotlib. It has several functions to manipulate your data as well as provide univariate and multivariate analysis. NOTE: The software is still an early beta. Please tell us if you found a bug. Download datasets for students of Geostatistics 2017 (Petroleum Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Petroleum.zip/download Download datasets for students of Geostatistics 2017 (Geology and Mining Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Mining.zip/download Old: http://sourceforge.net/projects/geoms2/files/SETS_geoestatistica2_2015.7z/download https://sites.google.com/site/cmrpsoftware/downloads/Quarry_sets.7z?attredirects=0&d=1 http://sourceforge.net/projects/geoms2/files/Mining.7z/download -
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FreeCeilo is an interface for Ceilometer CL-31.It works in offline mode. It plots backscatter intensity, cloud base graph and surface plot.It was tested and developed at SPACE, Thiruvananthapuram, and is implemented in CESS.
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This application provides a web based visual browser for NetCDF files. The application provides a simple and friendly user interface for getting a quick overview of the data contained in the files.
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UV-CDAT
Ultrascale Visualization Climate Data Analysis Tools
Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT), is a powerful and complete front-end to a rich set of visual-data exploration and analysis capabilities well suited for climate-data analysis problems. -
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jif3d
3D Joint Inversion Framework
jif3d is a framework for joint inversion of different types of geophysical data in 3D. It currently comprises forward solvers for first arrival traveltimes, scalar and tensor gravity data, magnetics, magnetotellurics, electrical resistivity tomography and surface waves.The framework is flexible in terms of the coupling approach between the different datasets. At the moment cross-gradient coupling, variation of information and deterministic parameter relationships are implemented. Other coupling approaches can be added relatively easily. -
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Graphical Forecast Editor
View and edit grids of meteorological values
Allows viewing and editing of weather data from weather models as two dimensional grids. Python scripting support hooks in the ingest, editing and product creation subsystems allow for customization. All network communication made through HTTP services. Enhanced version of the system used by national weather services. -
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ccplot
CloudSat and CALIPSO plotting tool
ccplot is an open source command-line program for plotting profile, layer and earth view data sets from CloudSat, CALIPSO and Aqua MODIS products. -
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Pysolar is a Python library for calculating the position of the sun relative to the earth as a function of latitude, longitude, and time. There is also code included for other problems related to the development of photovoltaic systems. Still in alpha.
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weewx weather software
Python program for getting the most from your weather station
WeeWX is a free, open source, software program, written in Python, which interacts with your weather station to produce graphs, reports, and HTML pages. Downloads can be found at http://weewx.com/downloads Development happens at https://github.com/weewx/weewx -
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The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
